code: def test_softmax_big_inputs(backend_default):
      np.random.seed(1)
  
      be = backend_default
      assert be.bsz >= 128, "This tests needs large batch size"
  
      act = Softmax()
      Nout = 1000  # 1000 input and output units to softmax
  
      # random inputs
      x_ = np.random.random((Nout, be.bsz))
  
      x = be.iobuf(Nout)
      # init input to softmax
      x[:] = x_
  
      # numpy softmax
      mx = np.max(x_, axis=0)
      ex = np.exp(x_ - mx)
      y_ = ex / np.sum(ex, axis=0)
  
      # in-place softmax on device
      x[:] = act(x)
  
      assert allclose_with_out(y_, x.get(), atol=0.0, rtol=1.0e-5)
  
imports: from math import tanh
  import numpy
  from neon import NervanaObject
  from neon.transforms import Identity, Rectlin, Softmax, Tanh, Logistic, Sign, PixelwiseSoftmax
  from utils import allclose_with_out
label_desc: Use image node_id 18 for calling a global function with example usage: test_softmax_big_inputs(backend_default) without return types